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>> Hello and welcome to theCUBE's coverage.
Here we are in the Lake House
at Databricks Data + AI Summit's CUBE coverage.
We are co-locating with Databricks' massive stage here.
This is their media hub central.
theCUBE is going to be here for two days,
wall to wall coverage.
I'm joined by our CUBE analyst,
new CUBE's Rob Strechay.
Rob, we've been on a tour since Cube Con Amsterdam.
What a whirlwind. >> Oh yeah.
>> And AI is center stage. >> Yes.
>> Great to see you.
>> It's data week too.
So this is really exciting to be here
and talking all about AI and data
and how it's really going to turn.
>> I just dropped an exclusive interview
I had with Matt Garman,
who was steering the ship of Amazon
to the promised land of generative AI.
Google had an event in Seattle, all developers.
Snowflake had an event in Las Vegas
and here in Databricks in San Francisco.
You got Databricks.
It's data week.
Everything's happening.
Everyone wants that prize.
The whole industry wants to win the mind share
of this massively surging developer community.
And we've said, Rob,
we've been on theCUBE record now for months.
Open source will win.
And you heard from Ali Ghodsi today on stage
it's very clear that open source
is a big theme of their history
and their future and their present.
And what what's more exciting is
he even dropped a few bombs out there by saying,
we're going to end the format wars with this uniform layer.
Bringing things together on the metadata.
I mean, bold move.
Databricks really accelerating the game in the open.
It's going to put a direct strike on Snowflake.
It's going to hopefully level the play field.
We'll see what's real.
We're going to dig into the analysis.
What was your take?
>> Yeah, I think it was really well put together.
I think there was a lot of
going through it at rapid pace today
and I think they were really looking at
how do they get to all of the content
they had to get through.
And I think a lot of it was around
how is generative AI going to develop
and how do you make it easier?
I think also it was unified governance
and how you can bring that together
and democratization of analytics as well.
And I think that's a big piece of it.
Those were kind of the three big themes
that they're taking with them taking forward.
>> One of the things I noticed, knowing Ali Ghodsi
since the beginning of Databricks,
he's been a candid Cube alumni.
He was a mix of super excited and nervous
because it was so crowded in there.
I've never seen that audience that big for Databricks.
He was delivering the Lakehouse positioning 3.0,
which was a combination of lake and house data warehouse.
It's interesting,
they're kind of reinventing data warehouse,
throwing the word lake around it.
But that's kind of their focus.
They're trying to get back into that world and modernize it,
create a unified layer.
And some things I liked was
the Delta sharing, the Unity catalog
and this format wars ending with uniform, their positioning.
I thought that was clever.
And just the sheer open source penetration, that has legs.
And I think the question will be, will that be adopted?
>> Yeah, I agree.
I think it's going to be interesting.
I think, Ali kind of pre-briefed us
a little bit yesterday on this stuff
and I asked some questions around some of these things
and I think one that you're mentioning
around the whole ending the war, it really,
it's on by default being able to do
all those three different formats.
Obviously Delta Lake is always there,
but the other two formats and bringing that in,
I think what's key about this
and what's going to be key in the future
is that it gives much more spread across there.
And if you look at some of the other announcements
that they're making,
they're really focused on how they have a control plane,
that data control plane going forward.
And I think that's where the battle lines have been
really underneath AI.
That's where the battle lines are being drawn
with them in Snowflake.
>> Well, we had Ali Ghodsi on our Supercloud event too.
Our original, I should say, on one, our inaugural event.
He was also a keynote exclusive
for our Reinvent coverage last year.
And now with this Databricks Data + AI,
every company will be a gen AI company.
And that's his focus.
You heard a lot of, not a lot of multicloud.
Cause we like to bring that term up, supercloud.
Having Microsoft's CEO Satya Nadella on stage
or remote in, Skyped in.
They still use that word Skype.
>> Rob: Right.
>> I'm not sure why they even keep that brand name,
but that's a whole 'nother story.
He was Skyped in and it was a very interesting dialogue.
One, two, it was not AWS, they're a big partner.
They're doing more business with with Azure.
So they're increasing their TAM.
Databricks clearly going multicloud.
So is Snowflake.
This super cloud dynamic is happening.
Little bit kind of a sub message
in the subtext of that kind of thing.
And I got to tell you, smart move by Databricks.
By expanding in with Microsoft,
they increase their total addressable market.
They increase their customer base.
JP Morgan Chase, again, joint customer of Microsoft.
Satya Nadella showing his chops,
his technical, bringing infrastructure knowledge,
Microsoft leaning in, winning the messaging war,
winning the marketing war.
It's pretty obvious to me
that Microsoft clearly is out gunning AWS right now
on the PR front.
Absolutely controlling the messaging
and causing other clouds to be on the defensive.
>> Yes, yeah, definitely.
They're reactive.
They're being reactive, all the rest of the clouds.
And I think we've seen that
over the last month and a half to two months even,
maybe even a little bit longer.
And I think really when you start to look at how Databricks
and Microsoft, their messaging,
it's really similar messaging
and how they're trying to bring LLMs to the masses
and how they're trying to really bring more out to them
and be really clear about, hey, here's how you make it easy.
And I think one of the big things was,
even though they're not calling it an assistant,
which is really,
they're inside of their lakehouse AI
and what they're trying to do with the assistant
that can help you build the queries for your lakehouse.
And I think that's key.
It's their version of copilot.
And there was a lot of talk with Satya about copilot,
which makes a lot of sense.
>> The other thing they announced was
the marketplace was a big part of their initiative.
Again, it's open to everyone
and they kind of dinged the clouds by saying lock in
and saying the cloud's only optimized for their clouds,
which is true.
>> Rob: Right.
>> So they're trying to build this
federated kind of marketplace to be open.
I thought that was interesting.
>> Rob: Yeah.
>> That combined with the Delta sharing protocol,
you got some interesting
open source power dynamics going on.
I think that's going to be something we're going to unpack a lot
over the next second half of the year, Rob.
>> I agree, I agree.
And not only that, but they're clean rooms initiatives,
which is that Delta sharing.
And when they started to look at Lakehouse apps,
which they didn't, Ali didn't really go into that much,
but we kind of talked about it a little bit yesterday,
which is again, under the hood it's Kubernetes.
And when you start to look at it,
it's going to help some Greenfield customers
extremely quickly get into a marketplace
and be able to have security and governance over that
by running on Databricks' infrastructure.
>> I always liked Databricks,
I always liked their approach,
I always liked the conversations,
but one thing that's notably different this event
is they're stepping up their game.
They got Moscone, 12,000 people, it's packed.
75,000 people online, both south and north packed venue.
Their brand, they're stepping up.
They could be a big player,
they could be the dominant player
in the modern data warehouse world,
which is essentially cloud, data cloud.
They could be the dominant player
for what we're talking about a lot here in theCUBE
is having data products in a marketplace.
And then ultimately the term we coined
called data developer, Rob.
>> Rob: Yeah.
Is really the emergence of what will be a new persona
if these dots connect, if Ali Ghodsi's vision,
combined with what Matt Garman told me in my exclusive
is that as this scale continues
from data infrastructure reset with generative AI,
the data products enabling a data developer,
those apps are going to come online.
They're going to be running on the cloud.
This will be a new power dynamic
and the developer will be in charge of the data.
We saw this with DevOps, we saw this with security now.
Shifting left,
the new power dynamic will be the data developer.
We're going to see it emerge in front of our eyes.
We'll be covering it like a blanket here on theCUBE.
>> Yeah.
I think the data developer joined with platform engineering
and what you have is them actually going out
and engineering that data control plane.
And I think with Lakehouse Federation,
one of the announcements today,
it's another one where both them and Snowflake are competing
for the heart and minds of both platform engineering
and that that data layer, data engineering layer, so.
>> Dave Vellante loves horse racing analogies,
so we have to go with one here.
A lot of horses on the track, they're clustered up,
they're all kind of jockeying for position.
They're all kind of in a pack right now.
Some are ahead, some are not.
But ultimately the other dynamic is
people might be switching horses.
>> Rob: Yes.
>> Amazon to Azure.
This model to that model, choice is becoming a huge factor
before putting things into production.
We're still in discovery phase with generative AI and LLMs
and foundation models.
So again, tapering down the hype, which is all time high.
>> Rob: Yeah.
>> Generative AI is a game changer.
However, it's early,
we're still in discovery mode with developers.
We're seeing people thinking about,
do I have the right horse for this?
Is this the right model for that?
How do I tune it and scale it?
How much is it going to cost?
Is it ethical?
Do I run it on the cloud?
These are all questions that are being asked here
and in the industry.
>> Yeah.
And it's fascinating with the customers that are here
and having some conversations with them already.
Really what they're betting on is
how are we going to be able to keep our data private?
That message was super strong in the keynote today
about privacy, about keeping your PII private,
being able to actually monitor that.
And I thought that was a neat little demo that they did.
As part of that, I think again,
there's a lot of hype around it.
There's a lot of things that need to be figured out.
>> A lot of swirling conversations around
which cloud's going to be the leader.
Databricks is not holding back.
They could be an emergent kind of supercloud layer
across all clouds.
Something that we've been tracking.
I had an interview with Matt Garman
who heads up Amazon's field and sales and operations,
former EC2.
So he's got technical chops,
kind of like Satya Nadella, flexing his chops.
I know Garmin's got some technology chops,
which is, it gives him a unique position.
He was echoing on my interview with him
some of the same points that Ali Ghodsi
was saying on stage.
And I want to get your reaction to these points,
if you don't mind.
One, the AI potential and ethical concerns.
>> Rob: Yeah.
>> I'll just run the list and we'll go through 'em.
Securing data, amplifying choice,
augmenting human capabilities with AI versus replacing them,
innovating around some constraints
and opportunities around GPUs.
Little nuanced point we heard today.
So let's start with AI ethics.
>> [Rob Yeah.
>> Of course, adoption and consumption of AI.
>> Rob: Right.
>> So let's start with the ethics piece.
What's your take?
What'd you hear here?
They kind of had the proverbial, Satya Nadella.
Whoa, we got to be careful.
>> Rob: Yeah, well.
>> You know how I feel about that.
>> I think it's everybody wants to be careful,
but I don't think anybody knows how to be careful yet.
And I think it's early days in figuring this out.
I think you'll see the industry come together
as regulation is ramping up.
I mean, you already have the first bill of regulation
going through the EU.
I think they have to get in line
and they have to nail the ethics part of this
because it's really key to not having it over regulated
or pushed back or stamped down.
>> I'll say what everyone's thinking.
I think it's virtue signaling.
I think it's BS.
I think there is no notion of regulation at this point.
We got to get this stuff out out of the garage
and into the streets, into production.
We got to watch it, monitor it.
That's the only issue.
Regulation is a bad path for AI.
I think that is complete horse you know what.
I think we got to avoid that.
I think everyone's just virtue signaling,
oh yeah, we got to be careful.
>> Rob: Yeah.
>> That's code words for don't regulate us.
So I think that that's one thing.
The other thing that's the ethical issue that comes up
that's not talked about is the intellectual property rights.
This is what Ali was all about today.
Your IP is your data.
>> Rob: Right.
>> And their entire thesis of Lakehouse is
don't put that into the LLM.
Matt Garman at AWS also echoed that sentiment.
Like, hey, that corpus is public.
Once the genie's out of the bottle,
you can't put that back in.
So this is a huge issue.
>> Rob: Yes.
>> Around data and then how the data engineering,
platform engineering has to now refactor
to drive these new data products.
>> Rob: Yeah
and I think even Satya brought it up with watermarking
and things like that and how do you deal with copyright?
How do you deal with intellectual property?
These are huge.
And I think that to your point, most people,
I was talking to a healthcare organization just earlier
before coming on here
and they were talking about how they're using Databricks,
but they're using it in a very private way
because you're talking about
people's healthcare information.
You got to be careful with that.
And right now you can't be using
these SaaS delivered public models that are proprietary
to go and do this
where you don't know where the data's going to end up.
>> I got to talk about adoption real quick.
Fostering consumption and adoption.
You heard that out there today.
They're trying to push ease of use within the platform.
These customers are diverse.
JP Morgan's different than a startup, right?
>> Rob: Yep.
So you have different diversity of solutions
that are needed from the infrastructure layer
all the way up to the application layer.
You're starting to see package solutions
and hardcore code, so.
>> Rob: Right.
>> Infrastructure silicon, GPUs, to the application stack
and everything in between is going to be a huge adoption.
>> Yeah.
And I think that they actually had
some really interesting stats on stage.
They're seeing from actual use inside of Databricks
where or two exabytes of data
is processed every day through Databricks.
And that in the last month they had
over 1,500 actual transformers
used within the Databricks environment.
That's showing you some of the adoption
and how it's really accelerating.
That's up from 400 just earlier on in the year.
>> So the other thing is cloud enabled growth,
one of the things that's come up is scale.
Ali didn't really talk about it in the keynote
'cause they're not the cloud, obviously they're in ISV.
>> Rob: Yeah.
>> But as far as Amazon's concerned,
but they got an ecosystem, 12,000 customers in person.
So as you look at the cloud enablement here,
you got to have the scale.
And again, if people are going to be switching horses,
how do you decide how to run this stuff, on cloud?
Do you run it on Databricks, on which cloud?
That becomes an interesting factor here.
The clouds are enabling at the end of the day
all this innovation.
>> Right, yeah.
And I think being across the clouds,
like you were talking about with supercloud,
it does give you that data layer,
that commonality of data layers across clouds.
And I think that is a big key.
They're not everywhere yet.
I mean there's still a lot of sovereign clouds
that can't get Databricks.
I think that that will be a challenge for them,
being that control plane long term.
But for a good portion of the companies and countries,
they actually do a good job of that.
>> And we heard about Mosaic ML with the GPUs.
>> Rob: Yeah.
>> Yeah, you and I found out through the grapevine
they got a stockpile of GPUs.
But a lot of CapEx to build out.
The GPUs are a big factor.
One of the reasons why
the cloud's looking good right now is AWS.
And I'm sure Azure's got a bunch of GPUs.
>> Rob: Yeah.
>> They can offload the GPU needs as a managed service
versus having it on site.
And that's an opportunity for Mosaic ML here with Databricks
on the training side.
>> Right, yeah, I think it is.
And I think where they're aiming to be the trainer,
the builder, the underlying,
I guess you could say infrastructure for AIML
versus trying to be the ultimate only model you use.
So it's the bring your own model concept.
But how do you get to success faster with your data?
That's where they're focused.
>> And final point is,
enterprise demands are very much in line here.
JP Morgan on stage amplifying,
almost gushing over Ali's celebrity-ism,
clearly a testimonial on stage.
I mean, he was basically a walking data sheet.
>> Rob: Yeah.
>> For Databricks, highlighting the advantages of Lakehouse.
It was almost as if he was reborn like, oh my God,
I came from the old way.
I thought that was a very telling interview.
>> Rob: Yeah.
Really showing the needs of the enterprise
is about governance
and nailing some of the things we were talking about
on our last Cube, which is nail those foundational elements
and then you can enable the value.
That's what the platforms offer.
Is that kind of enablement,
that's a huge part of Ali's talk today.
>> Yeah, I think they had Unity catalog weaved within
and throughout the entire keynote.
And I think that they're standing on that
as a differentiator for them
and how they bring that to market over all the data layer.
>> What's your final thoughts on the interview?
What'd you give it, a grade?
How would you rank it?
Obviously they had a lot to go through.
What's your thoughts?
>> I'd give us a solid B.
I'd say we will be bringing it up a notch
as we go through the day and get with some more people
and get some more interesting content going.
But I think we again,
we covered all of the interesting facts.
>> No, I'm talking about their keynote.
>> Oh, their keynote.
>> No, we're A.
Come on, what are you talking about B?
>> I'm a hard grader.
>> We always got the A game on.
>> I would say, I'd give Ali, I mean, again,
they had so much to try to unpack.
I think that it got a little muddled at times,
but I'd give them a B, I think it was really good.
>> I gave 'em a solid A minus.
'cause it's hard to get an A out of.
>> Rob: Yeah.
>> I gave 'em an A minus because, and pushing an A,
only because I thought they had the clock,
they had a clock problem.
So much to go through.
I gave him an A minus
because one, JP Morgan was an incredible guest,
the way they were just glowing with testimonials.
That's not staged.
That's real. >> Rob: Yeah.
>> That's authentic.
I can squint through that
and say that was pretty real, happy customer.
His positioning was amazing.
The Mosaic ML acquisition on the heels of the event
was a home run for Databricks.
The venue, the posture, they're standing tall right now.
And if you're Snowflake, you got to wonder.
There's almost two types of companies here,
Databricks, Snowflake, both with different vibes.
And you got to look at that and say, hmm.
It's like the Republicans and the Democrats.
It's like, who's on side you going to pick?
>> Rob: Yeah.
>> And they both worked together though,
so I thought that was a great move by them.
And the content was very developer education focused
without placating to the crowd too much.
They weren't talking down to the crowd.
They aligned with the developers.
I think this data developer theme
is right on point for them.
I think they're going to wake up
and realize that they have an ecosystem
that's going to be with them for the next 20 years.
And so that room was very much aligned
with some of the early days of VMware where you.
>> Rob: Right.
>> There's a lot of demos, a lot of learning.
So I thought a minus for sure, pushing an A.
But again, the clock was tight.
>> Rob: Yeah.
>> They had to go fast.
Overall, great event.
>> Yeah, I agree.
I thought it was very energizing to say the least.
>> All right.
That's theCUBE's keynote analysis here inside the Lakehouse
on the floor of the Databricks AI + Data Events Summit.
And you get the theCUBE ongoing coverage,
two days wall to wall.
I'm Sean Furrier with Rob Strechay.
We'll be right back with our next guest
after this short break.
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